2 citations · 7 across the 21 of their papers we have counts for
5 papers · 1 filter
PromptTA: Prompt-driven Text Adapter for Source-free Domain Generalization
Haoran Zhang, Shuanghao Bai, Wanqi Zhou +2
Source-free domain generalization (SFDG) tackles the challenge of adapting models to unseen target domains without access to source domain data. To deal with this challenging task,…
Jacobian Regularizer-based Neural Granger Causality
Wanqi Zhou, Shuanghao Bai, Shujian Yu +2
With the advancement of neural networks, diverse methods for neural Granger causality have emerged, which demonstrate proficiency in handling complex data, and nonlinear relationsh…
Revisiting the Adversarial Robustness of Vision Language Models: a Multimodal Perspective
Wanqi Zhou, Shuanghao Bai, Danilo P. Mandic +2
Pretrained vision-language models (VLMs) like CLIP exhibit exceptional generalization across diverse downstream tasks. While recent studies reveal their vulnerability to adversaria…
Soft Prompt Generation for Domain Generalization
Shuanghao Bai, Yuedi Zhang, Wanqi Zhou +2
Large pre-trained vision language models (VLMs) have shown impressive zero-shot ability on downstream tasks with manually designed prompt. To further adapt VLMs to downstream tasks…
Prompt-based Distribution Alignment for Unsupervised Domain Adaptation
Shuanghao Bai, Min Zhang, Wanqi Zhou +4
Recently, despite the unprecedented success of large pre-trained visual-language models (VLMs) on a wide range of downstream tasks, the real-world unsupervised domain adaptation (U…